Counterfactual Explanations

What are counterfactual explanations?

A counterfactual explanation reveals what should have been different in an instance to observe a diverse outcome. Counterfactual explanations describe a particular situation in the following template: “If X had not occurred, Y would not have occurred.”

For example, consider a machine learning model that approves or rejects a loan proposal based on an applicant’s income. Let’s say the loan was approved for an applicant with an annual income of $50,000 and a good credit history.

A counterfactual explanation to this model decision would look like this: “If the applicant’s annual income had not been $45,000, their loan would be denied.” This tells us that an annual income of $45,000 is necessary for the loan to get approved (even when the applicant has good credit history), explaining why the loan was approved.